ColossalAI/tests/test_zero/test_gemini/test_search.py

64 lines
1.9 KiB
Python

import pytest
import torch
import colossalai
from colossalai.testing import rerun_if_address_is_in_use, spawn
from colossalai.utils import get_current_device
from colossalai.zero.gemini.chunk import init_chunk_manager, search_chunk_configuration
from tests.kit.model_zoo import model_zoo
def exam_search_chunk_size():
model_builder, data_gen_fn, output_transform_fn, *_ = next(
iter(model_zoo.get_sub_registry("transformers_gpt_lm").values())
)
# make sure torch_model and model has the same parameter values
model = model_builder()
config_dict, *_ = search_chunk_configuration(
model, search_range_m=1, search_interval=128, min_chunk_size_m=0, filter_exlarge_params=True
)
for key in config_dict:
chunk_size = config_dict[key]["chunk_size"]
assert chunk_size == 527872
def exam_chunk_manager():
world_size = torch.distributed.get_world_size()
model_builder, data_gen_fn, output_transform_fn, *_ = next(
iter(model_zoo.get_sub_registry("transformers_gpt_lm").values())
)
sharded_ddp_model = model_builder()
chunk_manager = init_chunk_manager(
sharded_ddp_model,
get_current_device(),
hidden_dim=128,
search_range_m=1,
min_chunk_size_m=0,
filter_exlarge_params=True,
strict_ddp_flag=True,
)
config_dict = chunk_manager.dp_degree_chunk_size_dict
assert len(config_dict) == 1
assert config_dict[world_size] == 527872
def run_dist(rank, world_size, port):
colossalai.launch(config={}, rank=rank, world_size=world_size, host="localhost", port=port, backend="nccl")
exam_search_chunk_size()
exam_chunk_manager()
@pytest.mark.dist
@pytest.mark.parametrize("world_size", [1, 4])
@rerun_if_address_is_in_use()
def test_search(world_size):
spawn(run_dist, world_size)
if __name__ == "__main__":
test_search(4)